A satellite assembly monitoring method and device, electronic equipment and storage medium

Abstract

This application relates to the field of satellite assembly technology, and in particular to a satellite assembly monitoring method, device, electronic device, and storage medium. The method includes real-time acquisition of the current completion status of each project node in satellite assembly; based on the current completion status of each project node and the corresponding overall progress, determining whether there are any abnormal project nodes; if abnormal project nodes exist, acquiring the process information of the abnormal project node, and determining the abnormal operation location based on the process information; the abnormal operation location is the sub-project node with an abnormality within the abnormal project node; acquiring abnormal image information at the abnormal operation location; and feeding back the abnormal image information to the terminal devices of relevant personnel. This application has the effect of timely detection of abnormalities occurring during satellite assembly and reducing the waste of human resources.

Description

Technical Field

[0001] This application relates to the field of satellite assembly technology, and in particular to a satellite assembly monitoring method, device, electronic equipment and storage medium. Background Technology

[0002] Satellites are primarily used for communication, navigation, and reconnaissance. With the booming development of the satellite industry, the role of satellites is receiving increasing attention, and the number of satellites launched is also increasing to meet people's needs. Before a satellite can be successfully launched, it needs to be assembled. Satellite assembly refers to a series of final assembly tasks that must be carried out from the satellite's pre-research and development design to simulation analysis and manufacturing. Every satellite must go through this stage before it can be successfully shipped out.

[0003] Satellite assembly is a complex process, consisting of multiple project nodes. Once all nodes are completed, the assembly is finished. However, satellite launches require significant human and financial resources, necessitating real-time monitoring of each node's progress. Currently, manual supervision is typically used to detect and resolve anomalies promptly. However, given the numerous and complex steps involved, the technical requirements for supervisors are high. Furthermore, the long assembly cycle means that assigning multiple highly skilled personnel for real-time monitoring could be wasteful of human resources. Summary of the Invention

[0004] In order to promptly detect anomalies during satellite assembly and reduce the waste of human resources, this application provides a satellite assembly monitoring method, device, electronic equipment, and storage medium.

[0005] Firstly, this application provides a satellite assembly monitoring method, which adopts the following technical solution:

[0006] A satellite assembly monitoring method, comprising:

[0007] Real-time acquisition of the current completion status of each project node in satellite assembly;

[0008] Based on the current completion status of each project node and the complete progress corresponding to each project node, determine whether there are any abnormal project nodes;

[0009] If there is an abnormal project node, the process information of the abnormal project node is obtained, and the abnormal operation location is determined according to the process information. The abnormal operation location is the abnormal sub-project node in the abnormal project node.

[0010] Obtain abnormal image information at the location of the abnormal operation;

[0011] The abnormal image information is then fed back to the terminal devices of the relevant personnel.

[0012] By adopting the above technical solution, the progress of each project node in the satellite assembly process is acquired in real time to monitor the assembly process. This allows for the timely detection of project nodes with abnormal completion rates. Reviewing the operational process information of these abnormal nodes helps determine the cause of the anomaly. Once the cause is identified, image information of the location of the anomaly is fed back to the terminal devices of relevant personnel. This allows them to view the specific situation at the location of the anomaly and quickly determine appropriate response strategies. Real-time monitoring of the satellite assembly work facilitates the timely detection of anomalies. Furthermore, by feeding back image information of the location of the anomaly to the terminal devices of relevant technicians, technicians can formulate timely response strategies, rather than requiring them to continuously monitor the assembly process. This helps to reduce the waste of human resources while promptly identifying anomalies.

[0013] In one possible implementation, the determination of whether there are abnormal project nodes based on the current completion status of each project node and the overall progress corresponding to each project node further includes:

[0014] Based on historical operation data, the operation nature of each project node is determined. The operation nature of each project node includes the difficulty distribution ratio of the assembly work of each project node. The difficulty distribution ratio is used to characterize the operation difficulty of each sub-project node in each project node.

[0015] The processing rate for each project node is determined based on the operational nature of each project node.

[0016] Specifically, based on the current completion status of each project node and the overall progress corresponding to each project node, it is determined whether there are any abnormal project nodes, including:

[0017] Based on the current completion status and corresponding full progress of each project node, determine the remaining workload of each project node.

[0018] Based on the remaining workload and corresponding processing efficiency of each project node, predict the remaining working time of each project node.

[0019] Based on the start time of each project node and the remaining working time, predict the completion date of each project node, where the start time is the working time required to complete the current completion status.

[0020] Based on the completion date of the project node and the standard completion date of the project node, determine whether the project node is an abnormal project node.

[0021] By adopting the above technical solution, the operational nature of each project node is determined based on historical operational data. This allows for the determination of the processing efficiency for each project node based on its operational nature. Furthermore, by considering the processing efficiency and the completed workload of each project node, the remaining workload and corresponding duration for that workload are determined, facilitating the determination of the project node's completion date. Comparing this completion date with the standard completion date helps identify any abnormalities in the project node's completion status. Real-time monitoring of the current completion status of each project node allows for real-time supervision of its work, enabling relevant personnel to promptly identify anomalies and coordinate the work of abnormal project nodes. This reduces the probability of project nodes exceeding their deadlines, and consequently, reduces the probability of satellite assembly work exceeding its deadlines.

[0022] In one possible implementation, determining the processing rate corresponding to each project node based on the operational nature of each project node includes:

[0023] Based on the ratio of easy to difficult operations for each project node, the operation level of each project node is divided into operation levels, where the operation level is directly proportional to the ratio of easy to difficult operations.

[0024] Based on the defined operation levels and historical operation data, the processing rate corresponding to each project node is determined. The historical operation data is used to characterize the historical processing rate of each project node in historical assembly work.

[0025] By adopting the above technical solution, when determining the processing efficiency of project nodes, the project nodes are first classified into levels based on their operational nature, i.e., operational difficulty, rather than relying solely on human experience to judge the difficulty of project nodes. The initial processing efficiency of project nodes can be determined based on the classified levels, and the initial processing rate of project nodes can be optimized using historical operation data, thereby improving the accuracy of determining the processing efficiency of project nodes.

[0026] In one possible implementation, obtaining the process information of the abnormal project node and determining the location of the abnormal operation based on the process information includes:

[0027] Based on the process information of the abnormal project node, determine at least one processing position corresponding to the abnormal project node;

[0028] Obtain operation information for each processing location, including operation time, operation result, and operation video; match the operation information for each processing location with the corresponding operation standard, and if they do not match, determine that the processing location as an abnormal operation location.

[0029] By adopting the above technical solution, the abnormal project node's process information can be used to identify the locations in the project node that may be abnormal, i.e., the sub-project nodes that may be abnormal. Data filtering can reduce the number of data comparisons when identifying abnormal sub-project nodes, thereby reducing the computational burden on the computer. Furthermore, by comparing the operation information corresponding to the sub-project nodes that may be abnormal with the standard operation information, the accuracy of identifying abnormal operation locations can be improved.

[0030] In one possible implementation, the method further includes:

[0031] Record the cause of abnormal operation corresponding to the abnormal operation position in each abnormal project node, and form multiple first matrix data, the first matrix data including the cause of abnormal operation at least one abnormal operation position corresponding to the abnormal project node;

[0032] Multiple first matrix data are integrated to obtain second matrix data, which includes at least one abnormal item node corresponding to the abnormal operation reason at the abnormal operation location;

[0033] The second matrix data is then fed back to the terminal devices of the relevant staff.

[0034] By adopting the above technical solution, the abnormal operation reasons of the sub-project nodes corresponding to each project node are integrated, making it easier to identify all project nodes where each abnormal operation reason occurs. This allows relevant personnel to uniformly optimize the assembly work of project nodes in satellite assembly based on the abnormal operation reasons, thereby improving the efficiency of satellite assembly work optimization.

[0035] In one possible implementation, obtaining the abnormal image information at the location of the abnormal operation includes:

[0036] Obtain a two-dimensional image of the location of the abnormal operation;

[0037] Determine the three-dimensional coordinates of the abnormal operation location based on the two-dimensional image;

[0038] Anomaly image information at the location of the abnormal operation is generated based on the three-dimensional coordinates.

[0039] By adopting the above technical solution, two-dimensional image information is converted into three-dimensional abnormal image information for feedback, which makes it easier for relevant personnel to clearly view the situation at the abnormal location through terminal devices. Furthermore, the three-dimensional abnormal image information allows relevant personnel to view the actual situation at the abnormal operation location, enabling them to feel as if they are there, thereby improving the efficiency of relevant technical personnel in determining response strategies.

[0040] In one possible implementation, the method further includes:

[0041] Obtain the satellite assembly process of the abnormal project node, and based on the obtained satellite assembly process, determine whether the abnormal project node has any influencing nodes, wherein the influencing nodes are project nodes that are related to the abnormal project node.

[0042] If it exists, then obtain the process information of the affected node;

[0043] The process information of the affected nodes is compared with the process standard information to generate a verification result, which is then fed back to the terminal devices of the relevant staff.

[0044] By adopting the above technical solution, when a project node with abnormal completion is detected, the satellite assembly process is used to determine whether there is an influencing node. If there is an influencing node, the process information of the influencing node is checked to facilitate timely coordination of the assembly work of the influencing node and to promptly detect situations where the completion of the influencing node is abnormal, thereby reducing the probability of schedule delays in the satellite assembly process.

[0045] Secondly, this application provides a satellite assembly monitoring device, which adopts the following technical solution:

[0046] A satellite assembly monitoring device, comprising:

[0047] The progress acquisition module is used to acquire the current completion status of each project node in the satellite assembly process in real time.

[0048] The anomaly detection module is used to determine whether there are any abnormal project nodes based on the current completion status of each project node and the corresponding complete progress of each project node.

[0049] The abnormal location determination module is used to obtain the process information of the abnormal project node if there is an abnormal project node, and determine the abnormal operation location based on the process information. The abnormal operation location is the sub-project node in the abnormal project node that has an abnormality.

[0050] An abnormal image acquisition module is used to acquire abnormal image information at the location of the abnormal operation;

[0051] An anomaly feedback module is used to feed back the abnormal image information to the terminal devices of relevant personnel.

[0052] By adopting the above technical solution, the progress of each project node in the satellite assembly process is acquired in real time to monitor the assembly process. This allows for the timely detection of project nodes with abnormal completion rates. Reviewing the operational process information of these abnormal nodes helps determine the cause of the anomaly. Once the cause is identified, image information of the location of the anomaly is fed back to the terminal devices of relevant personnel. This allows them to view the specific situation at the location of the anomaly and quickly determine appropriate response strategies. Real-time monitoring of the satellite assembly work facilitates the timely detection of anomalies. Furthermore, by feeding back image information of the location of the anomaly to the terminal devices of relevant technicians, technicians can formulate timely response strategies, rather than requiring them to continuously monitor the assembly process. This helps to reduce the waste of human resources while promptly identifying anomalies.

[0053] In one possible implementation, the device further includes:

[0054] The operation nature determination module is used to determine the operation nature of each project node based on historical operation data. The operation nature of each project node includes the difficulty distribution ratio of the assembly work of each project node. The difficulty distribution ratio is used to characterize the operation difficulty of each sub-project node in each project node.

[0055] The processing rate determination module is used to determine the processing rate corresponding to each project node based on the operational nature of each project node. Specifically, the anomaly detection module, when determining whether there are abnormal project nodes based on the current completion status and the overall progress of each project node, is used for:

[0056] Based on the current completion status and corresponding full progress of each project node, determine the remaining workload of each project node.

[0057] Based on the remaining workload and corresponding processing efficiency of each project node, predict the remaining working time of each project node.

[0058] Based on the start time of each project node and the remaining working time, predict the completion date of each project node, where the start time is the working time required to complete the current completion status.

[0059] Based on the completion date of the project node and the standard completion date of the project node, determine whether the project node is an abnormal project node.

[0060] In one possible implementation, the processing rate determination module, when determining the processing rate for each project node based on the operational nature of each project node, is specifically used for:

[0061] Based on the ratio of easy to difficult operations for each project node, the operation level of each project node is divided into operation levels, where the operation level is directly proportional to the ratio of easy to difficult operations.

[0062] Based on the defined operation levels and historical operation data, the processing rate corresponding to each project node is determined. The historical operation data is used to characterize the historical processing rate of each project node in historical assembly work.

[0063] In one possible implementation, when the abnormal location determination module acquires the process information of the abnormal project node and determines the abnormal operation location based on the process information, it is specifically used for:

[0064] Based on the process information of the abnormal project node, determine at least one processing position corresponding to the abnormal project node;

[0065] Obtain operation information for each processing location, including operation time, operation result, and operation video; match the operation information for each processing location with the corresponding operation standard, and if they do not match, determine that the processing location as an abnormal operation location.

[0066] In one possible implementation, the device also includes:

[0067] A first matrix generation module is used to record the cause of abnormal operation corresponding to the abnormal operation position in each abnormal project node, and to form multiple first matrix data, wherein the first matrix data includes the cause of abnormal operation at least one abnormal operation position corresponding to the abnormal project node.

[0068] A second matrix generation module is used to integrate multiple first matrix data to obtain second matrix data, wherein the second matrix data includes at least one abnormal item node corresponding to the abnormal operation reason at the abnormal operation location;

[0069] The matrix data feedback module is used to feed back the second matrix data to the terminal devices of relevant staff.

[0070] In one possible implementation, when the abnormal image acquisition module acquires abnormal image information at the location of the abnormal operation, it is specifically used for:

[0071] Obtain a two-dimensional image of the location of the abnormal operation;

[0072] Determine the three-dimensional coordinates of the abnormal operation location based on the two-dimensional image;

[0073] Anomaly image information at the location of the abnormal operation is generated based on the three-dimensional coordinates.

[0074] In one possible implementation, the device further includes:

[0075] The module for identifying influencing nodes is used to obtain the satellite assembly process of abnormal project nodes and, based on the obtained satellite assembly process, determine whether there are influencing nodes for the abnormal project nodes. The influencing nodes are project nodes that are associated with the abnormal project nodes.

[0076] The module for obtaining information about affected nodes is used to obtain the process information of the affected nodes if there are affected nodes in the abnormal project node.

[0077] The information feedback module is used to verify the process information of the affected nodes with the process standard information, generate a verification result, and feed the verification result back to the terminal device of the relevant staff.

[0078] Thirdly, this application provides an electronic device that adopts the following technical solution:

[0079] An electronic device comprising:

[0080] At least one processor;

[0081] Memory;

[0082] At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application being configured to: perform the above-described method for monitoring satellite assembly.

[0083] Fourthly, this application provides a computer-readable storage medium, which adopts the following technical solution:

[0084] A computer-readable storage medium includes: a computer program stored thereon that can be loaded by a processor and execute the above-described satellite assembly monitoring method.

[0085] In summary, this application includes at least one of the following beneficial technical effects:

[0086] 1. By acquiring the progress of each project node in the satellite assembly process in real time, the assembly process can be monitored in real time. This allows for the timely detection of project nodes with abnormal completion rates. Reviewing the operational process information of these abnormal project nodes helps determine the cause of the abnormality. Once the cause of the abnormal operation is identified, image information of the location of the abnormality is fed back to the terminal devices of relevant personnel. This allows them to view the specific situation at the location of the abnormal operation and quickly determine the corresponding response strategy. Real-time monitoring of the satellite assembly work facilitates the timely detection of anomalies. When an anomaly occurs, image information of the corresponding location is fed back to the terminal devices of relevant technical personnel, enabling them to take timely action. This avoids the need for technical personnel to continuously monitor the satellite assembly process, thus helping to detect anomalies promptly and reducing the waste of human resources.

[0087] 2. Based on historical operational data, determine the operational nature of each project node. This allows for the determination of the processing efficiency for each project node. Then, by analyzing the processing efficiency and completed workload of each project node, determine the remaining workload and corresponding duration, thus facilitating the determination of the project node's completion date. Compare the completion date with the standard completion date to identify any abnormalities in the project node's completion status. Real-time monitoring of the current completion status of each project node allows for real-time supervision of its work, enabling relevant personnel to promptly identify anomalies and coordinate the work of abnormal project nodes. This reduces the probability of project node work exceeding the deadline, thereby reducing the likelihood of satellite assembly work exceeding the deadline. Attached Figure Description

[0088] Figure 1 This is a flowchart illustrating a satellite assembly monitoring method according to an embodiment of this application;

[0089] Figure 2 This is a schematic diagram of the connection relationship between project nodes in an embodiment of this application;

[0090] Figure 3 This is a schematic diagram of the structure of a satellite assembly monitoring device according to an embodiment of this application;

[0091] Figure 4 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0092] The following is in conjunction with the appendix Figure 1-4 This application will be described in further detail.

[0093] After reading this specification, those skilled in the art may make modifications to this embodiment without contributing any inventive step, but such modifications are protected by patent law as long as they fall within the scope of the claims of this application.

[0094] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0095] To promptly detect anomalies during satellite assembly and reduce the waste of human resources, this application embodiment acquires the progress of each project node in the satellite assembly process in real time for real-time monitoring. This facilitates the timely detection of project nodes with abnormal completion rates. By reviewing the operational process information of project nodes with abnormal completion rates, the cause of the anomaly can be determined. After identifying the cause of the abnormal operation, image information of the location of the anomaly is fed back to the terminal devices of relevant personnel, allowing them to view the specific situation at the location of the abnormal operation and quickly determine the corresponding response strategy. By monitoring the satellite assembly work in real time, anomalies can be detected promptly, and when an anomaly occurs, image information of the location of the abnormal operation is fed back to the terminal devices of relevant technicians, enabling them to take timely response strategies, rather than requiring technicians to continuously monitor the satellite assembly process in real time.

[0096] Specifically, this application provides a satellite assembly monitoring method executed by an electronic device, which can be a server or a terminal device. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smartphone, tablet, laptop, desktop computer, etc., but is not limited to these. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, and this application does not impose any limitations on this connection.

[0097] refer to Figure 1 , Figure 1 This is a flowchart illustrating a satellite assembly monitoring method according to an embodiment of this application. The method includes steps S110, S120, S130, S140, and S150, wherein:

[0098] Step S110: Obtain the current completion status of each project node in the satellite assembly in real time.

[0099] Specifically, satellite assembly is a crucial step in satellite manufacturing quality control. Since satellite launches require significant financial and material resources, any abnormalities during assembly can lead to malfunctions during post-launch operation. Therefore, the satellite assembly process is extremely important. Every satellite must undergo the satellite assembly stage before it can be successfully manufactured and launched. Satellite assembly involves adjusting the equipment of each subsystem, fixing the equipment used in each subsystem to its corresponding position, and connecting the equipment of each subsystem using cables and conduits to form a satellite whose quality characteristics, accuracy, and airtightness meet the requirements for satellite launch.

[0100] To improve the efficiency of satellite assembly, multiple project nodes may operate simultaneously. This involves adjusting and combining equipment from multiple subsystems at the same time, followed by assembling the related subsystem equipment to complete the satellite assembly. Since each project node involves different operations, and the progress of each node's operations can affect the overall satellite assembly progress, monitoring the current completion status of each project node is crucial for effective satellite assembly supervision.

[0101] The current completion status of each project node in satellite assembly can be determined by the corresponding data recording device at each project node. The data recording device can be an image acquisition device or a data entry device. When the data recording device is an image acquisition device, the electronic device can determine the current completion status of the project node through the received image information. When the data recording device is a data entry device, the electronic device can determine the current completion status of the project node through the entered data. When entering data, it can be done manually by staff located at the project node or automatically by machines at the project node.

[0102] Step S120: Based on the current completion status of each project node and the complete progress corresponding to each project node, determine whether there are any abnormal project nodes.

[0103] Specifically, the complete progress of a project node refers to the total amount of work done in completing satellite assembly for that node. The total amount of work for each project node can be determined by user input or by historical satellite assembly information. When comparing the current completion rate of a project node with its complete progress, comparisons can be made using work duration and efficiency. For example, a project node may include design drawings, model making, model optimization, and model assembly, with a complete progress of 100% and an operation period of 100 days. This includes 20 days for design drawings, 30 days for model making, 30 days for model optimization, and 20 days for model assembly. Currently, this project node has completed design drawings and model making, with a current completion rate of 50%, but the operation period is 80 days. The project node completion rate does not correspond to the operation period, therefore, this project node is identified as an abnormal project node.

[0104] Step S130: If there is an abnormal project node, obtain the process information of the abnormal project node and determine the location of the abnormal operation based on the process information.

[0105] The abnormal operation location is a sub-project node within an abnormal project node that contains an abnormal sub-project node.

[0106] Specifically, the process information refers to the information of each operation step when a project node is performing satellite assembly work. For example, when an abnormal project node A includes design drawings, model making, model optimization, and model assembly, the process information of the abnormal project node A is the process information of the corresponding operations when completing the design drawing sub-project node, model making sub-project node, model optimization sub-project node, and model assembly sub-project node, such as the start time and completion time of the operation. The process information makes it easier to determine the abnormal operation location in the abnormal project node A. When the operation starts too early or too late, or the operation ends too early or too late, an abnormality may occur.

[0107] Step S140: Obtain abnormal image information at the location of the abnormal operation.

[0108] Specifically, abnormal image information includes information about the location of abnormal operations. This information can be collected by an image acquisition device located at the abnormal operation location and uploaded to an electronic device.

[0109] Step S150: Feedback the abnormal image information to the terminal devices of relevant personnel.

[0110] Specifically, the abnormal image is fed back to the terminal device of the relevant personnel so that they can view the location of the abnormality. The terminal device of the relevant personnel can be a display screen or VR glasses. The specific terminal device is not specifically limited in this embodiment of the application, as long as it can display the abnormal image information.

[0111] In this embodiment of the application, the progress of each project node in the satellite assembly process is acquired in real time to monitor the satellite assembly process in real time. This allows for the timely detection of project nodes with abnormal completion rates. By reviewing the operational process information of project nodes with abnormal completion rates, the cause of the abnormal completion rate can be determined. After determining the cause of the abnormal operation, the image information of the location where the abnormal operation occurred is fed back to the terminal device of the relevant personnel. This allows the relevant personnel to view the specific situation at the location of the abnormal operation and quickly determine the response strategy. By monitoring the satellite assembly work in real time, it is easy to detect abnormalities in the satellite assembly work in a timely manner. When an abnormality occurs, the image information of the location of the abnormal operation is fed back to the terminal device of the relevant technicians, so that the relevant technicians can make timely response strategies, rather than having the relevant technicians continuously monitor the satellite assembly process in real time. This helps to detect abnormalities in a timely manner and reduce the waste of human resources.

[0112] In one possible implementation, to improve the accuracy of identifying abnormal project nodes, step S120 determines whether there are abnormal project nodes based on the current completion status of each project node and the corresponding overall progress. This is preceded by steps Sa1 (not shown in the attached figures) and Sa2 (not shown in the attached figures), wherein:

[0113] Step Sa1: Determine the operational nature of each project node based on historical operation data.

[0114] The operational nature of each project node includes the difficulty distribution ratio of the assembly work in each project node. The difficulty distribution ratio is used to characterize the operational difficulty of each sub-project node in each project node.

[0115] Specifically, historical operation data refers to the operational data saved during the historical satellite assembly process. The operational nature of project nodes characterizes the difficulty level of each sub-project node in the assembly operation. For example, when project node A includes multiple sub-project nodes—design drawings, model making, model optimization, and model assembly—based on historical operation data, the operational nature of the design drawings, model making, and model optimization sub-project nodes is determined to be difficult, while the operational nature of the model assembly sub-project node is determined to be easy. Therefore, the operational nature of project node A is determined to be difficult initially and easy later. Thus, during the satellite assembly work at project node A, more time may be spent in the early stages, and less time may be spent in the later stages.

[0116] The operational nature of a project node can be determined by identifying similar project nodes from historical operation data and obtaining the number of workers and processing time for these similar project nodes during satellite assembly. A higher number of workers and a longer processing time indicate a more difficult operation for each sub-project node within the project node. Specifically, for project nodes where both the number of workers and the processing time exceed a preset standard value, the operational nature of the corresponding sub-project nodes is determined to be difficult. The preset standard value can be input by the user.

[0117] Step Sa2: Determine the processing rate corresponding to each project node based on the operational nature of each project node.

[0118] Specifically, the operational nature of a project node corresponds to its processing rate. When the operational nature of a sub-project node within a project node is difficult, the corresponding processing rate of the sub-project node is also relatively slow.

[0119] The process involves determining whether there are any abnormal project nodes based on the current completion status and the overall progress corresponding to each project node. This includes steps Sb1 (not shown in the attached diagram), Sb2 (not shown in the attached diagram), Sb3 (not shown in the attached diagram), and Sb4 (not shown in the attached diagram), where:

[0120] Step Sb1: Determine the remaining workload for each project node based on its current completion status and corresponding overall progress.

[0121] Specifically, the current completion status of a project node represents the amount of work completed since the project node started. The complete progress is the total amount of work that needs to be completed when the project node is completed. The remaining work and the completed work corresponding to the current completion status constitute the total work corresponding to the complete progress. Each project node corresponds to a complete progress, and the complete progress of each project node is composed of the progress of at least one sub-project node contained in each project.

[0122] Step Sb2: Determine the remaining working time for each project node based on the remaining workload and corresponding processing efficiency of each project node.

[0123] Specifically, each project node has a different processing efficiency. Based on the processing efficiency and remaining workload of each project node, the remaining working time of each project node can be determined. For example, if the processing efficiency of project node A is 10 days to complete 5% of the total workload, then it would take 200 days to complete the total workload of project node A. If the remaining workload is 25%, then based on the processing efficiency of project node A, the remaining working time of project node A can be determined to be 50 days.

[0124] Step Sb3: Determine the completion date of each project node based on the start time and remaining working time. The start time is the working time required to complete the current completion status.

[0125] Specifically, the start time is the time consumed to complete the current completion status of the project node, the remaining work time is the work time required to complete the remaining work, and the completion date is the date on which the remaining work of the project node is completed. For example, if the start date of project node A is March 21, the start time is 40 days, and the remaining work time is 20 days, then the completion date of the project node is May 20.

[0126] Step Sb4: Determine whether a project node is an abnormal project node based on its completion date and standard completion date.

[0127] Specifically, abnormal project nodes are those whose completion dates have exceeded the standard completion date. When the project processing efficiency is lower than the standard processing efficiency, it may cause the project node processing time to be too long, thus leading to the project node exceeding the deadline. The standard processing efficiency of a project node is determined based on the processing efficiency of similar project nodes in historical operation data. In actual satellite assembly work, human or non-human factors may cause the processing efficiency to be lower than the standard processing efficiency. For example, the standard processing efficiency of project node A is 10 days to complete 5% of the total workload. According to the standard processing efficiency, the entire workload can be completed in 200 days. However, due to human factors, in the actual satellite assembly work, it took 15 days to complete 5% of the entire workload. Therefore, to complete the entire workload, 300 days are needed, and the corresponding completion date will be delayed by 100 days, exceeding the standard completion date. In this case, project node A is determined to be an abnormal project node. Non-abnormal project nodes are those whose completion dates are within the standard completion date.

[0128] In this embodiment of the application, the operation nature corresponding to each project node is determined based on historical operation data. This allows for the determination of the processing efficiency of each project node based on the operation nature. Then, by using the processing efficiency of each project node and the completed workload of each project node, the remaining workload of the project node and the corresponding duration of the remaining workload are determined. This facilitates the determination of the completion date of the project node. The completion date is compared with the standard completion date to determine whether there are any abnormalities in the completion of the project node. By monitoring the current completion status of the project node in real time, the work status of each project node can be monitored in real time. This allows relevant personnel to promptly identify abnormalities and coordinate the work of abnormal project nodes in a timely manner, thereby reducing the probability of project node work exceeding the deadline, and thus reducing the probability of satellite assembly work exceeding the deadline.

[0129] Furthermore, to improve the processing efficiency of determining project nodes, step Sa2 determines the processing rate corresponding to each project node based on its operational nature. This specifically includes steps Sb21 (not shown in the attached figures) and Sb22 (not shown in the attached figures), wherein:

[0130] Step Sb21: Divide each project node into operation levels according to the ratio of easy to difficult operations, where the operation level is directly proportional to the ratio of easy to difficult operations.

[0131] Specifically, the operation level is determined by the ratio of the difficulty level of each sub-project node in the project node. For example, project node A includes multiple sub-project nodes, namely sub-project node 1, sub-project node 2, sub-project node 3, sub-project node 4 and sub-project node 5. Among them, the operation nature of sub-project node 1, sub-project node 2, sub-project node 3 and sub-project node 4 is difficult, and the operation nature of sub-project node 5 is easy. Therefore, the ratio of difficulty level to easy operation nature in project node A is 4:1.

[0132] The higher the ratio of easy to difficult operations, the higher the corresponding operation level. For example, if the ratio of easy to difficult operations for project node A is 4:1 and the ratio of easy to difficult operations for project node B is 5:1, then the operation level of project node B is higher than that of project node A. The specific correspondence between the ratio of easy to difficult operations and the operation level can be entered by the user.

[0133] In addition, the operation level of a project node can be determined by counting the number of sub-project nodes with difficult operation characteristics in each project node. The specific correspondence between the number of sub-project nodes and the operation level of the project node can be input by the user.

[0134] Step Sb22: Determine the processing rate for each project node based on the defined operation levels and historical operation data.

[0135] Specifically, each operation level corresponds to a different initial processing rate. The operation level and the initial processing rate are inversely proportional. The higher the operation level, the more difficult the operation of the project node, and the lower the corresponding initial processing efficiency. The correspondence between operation level and initial processing efficiency can be input by the user.

[0136] Historical operation data facilitates the optimization of the determined initial processing rate to obtain the final processing efficiency. The final processing efficiency may or may not be the same as the initial processing efficiency. Optimizing the initial processing efficiency of project nodes using historical operation data helps improve the accuracy of determining the processing efficiency of project nodes.

[0137] In the embodiments of this application, when determining the processing efficiency of a project node, the project node is first classified into levels based on its operational nature, i.e., operational difficulty, rather than relying solely on human experience to judge the difficulty of the project node. By classifying the levels, the initial processing efficiency of the project node can be determined. Then, the initial processing rate of the project node is optimized using historical operation data, thereby improving the accuracy of determining the processing efficiency of the project node.

[0138] In one possible implementation, step S130 obtains the process information of the abnormal project node and determines the location of the abnormal operation based on the process information. Specifically, this may include steps Sc1 (not shown in the attached figures), Sc2 (not shown in the attached figures), and Sc3 (not shown in the attached figures), wherein:

[0139] Step Sc1: Based on the process information of the abnormal project node, determine at least one processing position corresponding to the abnormal project node.

[0140] Specifically, abnormal project nodes are project nodes with abnormal completion rates. The process information of abnormal nodes includes the process information of each sub-project node in the project node during the satellite assembly work.

[0141] Step Sc2: Obtain the operation information for each processing location, including operation time, operation result, and operation video.

[0142] Specifically, the operation information for each processing location, i.e., the operation information for each sub-project node within the project node, can be obtained through the work log. The operation time is the start and end time of the sub-project node's work, and the operation result is the result after the sub-project node completes its corresponding work. Operation videos can be captured by an image acquisition device set at the sub-project node's area and uploaded to an electronic device. For example, when the sub-project node is a design drawing, the operation time is the start and end time of the design, the operation result is the completed design drawing, and the operation video records the entire design process.

[0143] Step Sc3: Match the operation information of each processing position with the corresponding operation standard. If they do not match, the processing position is determined to be an abnormal operation position.

[0144] Specifically, operational standards can be determined based on historical operational data. Similar project nodes are identified from this data, and their corresponding operational information is used as the operational standards for the current project node. Operation time limits are used to restrict the time allotted for project nodes, reducing the probability of timeouts. Operation results and videos facilitate the monitoring of project node work quality. Operation standards can also be user-inputted; for example, users can limit the working time of a specific project node based on the overall progress of satellite assembly. An abnormal node has at least one processing location; that is, a project node with an abnormal progress corresponds to at least one sub-project node.

[0145] For example, project node A includes four sub-project nodes: sub-project node 1, sub-project node 2, sub-project node 3, and sub-project node 4. When project node A has an abnormal completion rate, project node A is an abnormal project node. After matching the operation information of each sub-project node with the corresponding operation standard, it is determined that the operation information of sub-project node 2 and sub-project node 3 does not match the corresponding standard operation information. Therefore, sub-project node 2 and sub-project node 3 are identified as abnormal operation locations.

[0146] In this embodiment of the application, the abnormal project node's process information is used to determine the possible abnormal locations within the project node, i.e., the possible abnormal sub-project nodes. Data filtering helps reduce the number of data comparisons when determining abnormal sub-project nodes, thereby reducing the computational burden on the computer. Furthermore, by comparing the operation information corresponding to the possible abnormal sub-project nodes with standard operation information, the accuracy of determining the abnormal operation location is improved.

[0147] Furthermore, to facilitate analysis of any anomalies by relevant personnel, the method also includes steps Sd1 (not shown in the attached figures), Sd2 (not shown in the attached figures), and Sd3 (not shown in the attached figures), wherein:

[0148] Step Sd1: Record the reason for the abnormal operation corresponding to the abnormal operation position of each abnormal project node, and form multiple first matrix data, which include at least one abnormal operation position corresponding to the abnormal project node.

[0149] Specifically, the first matrix is ​​used to statistically analyze the reasons for abnormal operations in the sub-project nodes corresponding to each abnormal project node. For example, project node A includes four sub-project nodes: sub-project node a1, sub-project node a2, sub-project node a3, and sub-project node a4. Sub-project nodes a2 and a3 represent the locations of abnormal operations. Since the operation information includes operation time, operation result, and operation video, the reasons for abnormal operations may include operation time being too long or too short, operation results not meeting standards, and non-standard operation procedures. The reasons for abnormal operations correspond to the operation information, and the matrix data corresponding to project node A in the first matrix may be as follows:

[0150] Project node A = [Operation time too long, operation process not standardized]

[0151] In this embodiment, it is assumed that the operation information corresponding to each project node includes operation time, operation result, and operation video. Therefore, different project nodes may have the same abnormal operation reasons. Thus, after integrating the abnormal operation reasons corresponding to multiple project nodes into matrix data, multiple matrix data are obtained. These multiple matrix data can be:

[0152]

[0153] Step Sd2: Integrate multiple first matrix data to obtain second matrix data, which includes at least one abnormal item node corresponding to the cause of the abnormal operation.

[0154] Specifically, the data in the second matrix can be:

[0155]

[0156] Step Sd3: Feed back the second matrix data to the terminal devices of the relevant staff.

[0157] Specifically, the second matrix data is fed back to the terminal device of the relevant staff. The feedback can be in the form of displaying the second matrix data or performing matrix operations on the second matrix data and feeding back the results. The form of feedback is not specifically limited in this embodiment of the application, as long as the second matrix data can be fed back.

[0158] In this embodiment of the application, by integrating the abnormal operation cause characteristics of the sub-project nodes corresponding to each project node, it is easy to identify all project nodes where each abnormal operation cause occurs. This facilitates relevant personnel to uniformly optimize the assembly work of project nodes in satellite assembly work based on the abnormal operation cause, thereby improving the efficiency of optimizing satellite assembly work.

[0159] In one possible implementation, obtaining the abnormal image information at the location of the abnormal operation in step S140 may specifically include steps Se1 (not shown in the figures), Se2 (not shown in the figures), and Se3 (not shown in the figures), wherein:

[0160] Step Se1: Obtain a two-dimensional image of the location of the abnormal operation.

[0161] Specifically, the two-dimensional image of the abnormal operation location is an environmental image of that location, which at least includes the operation process at the abnormal operation location. The two-dimensional image of the abnormal operation location can be acquired by an image acquisition device positioned at the location and uploaded to an electronic device.

[0162] Step Se2: Determine the three-dimensional coordinates of the abnormal operation location based on the two-dimensional image.

[0163] Specifically, converting a two-dimensional image into three-dimensional coordinates means using the two-dimensional image to reconstruct a three-dimensional model. When determining the three-dimensional coordinates based on the two-dimensional image, a reference object can be determined first, and multiple views of the reference object can be determined based on the two-dimensional image. By taking any vertex in the reference image as a reference point, and using multiple views of the reference object, the three-dimensional vertex coordinates of the reference object can be determined. Based on the three-dimensional vertex coordinates of the reference object, it is convenient to determine the three-dimensional coordinates of other features in the two-dimensional image, thereby forming the three-dimensional coordinates of the abnormal operation location.

[0164] Step Se3: Generate abnormal image information at the location of the abnormal operation based on the three-dimensional coordinates.

[0165] Specifically, abnormal image information is fed back to the terminal devices of relevant staff so that they can view the situation at the abnormal location in a timely manner. The abnormal image can be a two-dimensional image or a three-dimensional image. After the three-dimensional abnormal image information is determined based on the three-dimensional coordinates, the three-dimensional abnormal image information is fed back to the virtual glasses of relevant staff so that they can be immersed in the situation.

[0166] In this embodiment of the application, by converting two-dimensional image information into three-dimensional abnormal image information for feedback, relevant personnel can clearly view the situation at the abnormal location through terminal devices, and view the actual situation at the abnormal operation location through three-dimensional abnormal image information, so that relevant personnel can be immersed in the situation, thereby improving the efficiency of relevant technical personnel in determining response strategies.

[0167] In one possible implementation, the method further includes steps S1 (not shown in the figures), S2 (not shown in the figures), and S3 (not shown in the figures), wherein:

[0168] Step S1: Obtain the satellite assembly process of the abnormal project node, and based on the obtained satellite assembly process, determine whether there are any influencing nodes for the abnormal project node. Influencing nodes are nodes that are linked with the abnormal project node.

[0169] Specifically, the satellite assembly process includes each project node involved in the satellite assembly process and the connections between each project node. The satellite assembly process facilitates the identification of any interconnected project nodes. To improve the efficiency of satellite assembly, simultaneous assembly tasks may occur. Related project nodes complete their respective assembly tasks before being combined and connected. If an abnormal completion rate is detected in a project node, related project nodes may also experience abnormal completion rates. For example... Figure 2 As shown, Figure 2 This is a schematic diagram of the connection relationship of project nodes in the satellite assembly process. Project nodes A, B, and C are independent of each other. Project node D is an influence node of project nodes A and B. Project node E is an influence node of project nodes A, B, C, and D. Project node G is an influence node of project nodes A, B, C, D, E, and F.

[0170] Step S2: If it exists, obtain the process information that affects the node.

[0171] Step S3: Verify the process information affecting the node with the process standard information, generate the verification result, and feed the verification result back to the terminal device of the relevant staff.

[0172] Specifically, the process of verifying the process information of the affected node against the standard information is similar to the process described above of matching the operation information of each processing position in the abnormal project node with the corresponding operation standard.

[0173] In the embodiments of this application, when a project node with abnormal completion is detected, the satellite assembly process is used to determine whether there is an influencing node. If there is an influencing node, the process information of the influencing node is checked to facilitate timely coordination of the assembly work of the influencing node and to promptly detect situations where the influencing node has abnormal completion, thereby reducing the probability of delays in the satellite assembly process.

[0174] The above embodiments describe a satellite assembly monitoring method from the perspective of process flow. The following embodiments describe a satellite assembly monitoring device from the perspective of virtual modules or virtual units. For details, please refer to the following embodiments.

[0175] This application provides a satellite assembly monitoring device, such as... Figure 3As shown, the device may specifically include a progress acquisition module 310, an anomaly judgment module 320, an anomaly location determination module 330, an anomaly image acquisition module 340, and an anomaly feedback module 350, wherein:

[0176] The progress acquisition module 310 is used to acquire the current completion status of each project node in the satellite assembly in real time.

[0177] The anomaly detection module 320 is used to determine whether there are any abnormal project nodes based on the current completion status of each project node and the complete progress corresponding to each project node.

[0178] The abnormal location determination module 330 is used to obtain the process information of the abnormal project node if there is an abnormal project node, and determine the abnormal operation location based on the process information. The abnormal operation location is the sub-project node in the abnormal project node that has an abnormality. The abnormal image acquisition module 340 is used to acquire abnormal image information at the abnormal operation location.

[0179] The anomaly feedback module 350 is used to feed back abnormal image information to the terminal devices of relevant personnel.

[0180] In one possible implementation, the device further includes:

[0181] The operation nature determination module is used to determine the operation nature of each project node based on historical operation data. The operation nature of each project node includes the difficulty distribution ratio of the assembly work of each project node. The difficulty distribution ratio is used to characterize the operation difficulty of each sub-project node in each project node.

[0182] The processing rate determination module is used to determine the processing rate corresponding to each project node based on the operational nature of each project node; wherein, the anomaly detection module 320, when determining whether there are abnormal project nodes based on the current completion status and the overall progress corresponding to each project node, is specifically used for:

[0183] Based on the current completion status and corresponding full progress of each project node, determine the remaining workload of each project node.

[0184] Based on the remaining workload and corresponding processing efficiency of each project node, predict the remaining working time of each project node.

[0185] Based on the start time and remaining working time of each project node, predict the completion date of each project node. The start time is the working time required to complete the current completion status.

[0186] Determine whether a project node is an abnormal project node based on its completion date and standard completion date.

[0187] In one possible implementation, the processing rate determination module, when determining the processing rate for each project node based on the operational nature of each project node, is specifically used for:

[0188] Based on the ratio of easy to difficult operations for each project node, the operation level of each project node is divided into operation levels, where the operation level is directly proportional to the ratio of easy to difficult operations.

[0189] Based on the defined operation levels and historical operation data, the processing rate corresponding to each project node is determined. The historical operation data is used to characterize the historical processing rate of each project node in the historical assembly process.

[0190] In one possible implementation, when the anomaly location determination module 330 acquires the process information of the anomaly item node and determines the location of the anomaly operation based on the process information, it is specifically used for:

[0191] Based on the process information of the abnormal project node, determine at least one processing position corresponding to the abnormal project node.

[0192] Obtain operation information for each processing location, including operation time, operation result, and operation video; match the operation information for each processing location with the corresponding operation standard, and if there is no match, determine that the processing location as an abnormal operation location.

[0193] In one possible implementation, the device also includes:

[0194] A first matrix generation module is used to record the cause of abnormal operation corresponding to the abnormal operation position in each abnormal project node, and to form multiple first matrix data. The first matrix data includes the cause of abnormal operation at least one abnormal operation position corresponding to the abnormal project node.

[0195] A second matrix generation module is used to integrate multiple first matrix data to obtain second matrix data, which includes at least one abnormal item node corresponding to the abnormal operation reason at the abnormal operation location.

[0196] The matrix data feedback module is used to feed back the second matrix data to the terminal devices of relevant staff.

[0197] In one possible implementation, when acquiring abnormal image information at the location of the abnormal operation, the abnormal image acquisition module 340 is specifically used for:

[0198] Obtain a two-dimensional image of the location of the abnormal operation;

[0199] Determine the three-dimensional coordinates of the abnormal operation location based on the two-dimensional image;

[0200] Anomaly image information at the location of the abnormal operation is generated based on three-dimensional coordinates.

[0201] In one possible implementation, the device further includes:

[0202] The module for identifying affected nodes is used to obtain the satellite assembly process of abnormal project nodes and, based on the obtained satellite assembly process, determine whether there are any affected nodes for the abnormal project nodes. Affected nodes are project nodes that are related to the abnormal project nodes. The module for obtaining affected node information is used to obtain the process information of the affected nodes if there are any affected nodes for the abnormal project nodes. The information feedback module is used to verify the process information of the affected nodes with the process standard information, generate the verification result, and feed the verification result back to the terminal devices of relevant personnel.

[0203] This application provides an electronic device, such as... Figure 4 As shown, Figure 4 The illustrated electronic device 400 includes a processor 401 and a memory 403. The processor 401 and the memory 403 are connected, for example, via a bus 402. Optionally, the electronic device 400 may also include a transceiver 404. It should be noted that in practical applications, the transceiver 404 is not limited to one type, and the structure of this electronic device 400 does not constitute a limitation on the embodiments of this application.

[0204] Processor 401 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 401 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0205] Bus 402 may include a pathway for transmitting information between the aforementioned components. Bus 402 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 402 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 4 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0206] The memory 403 may be a ROM (Read Only Memory) or other type of static storage device capable of storing static information and instructions, RAM (Random Access Memory) or other type of dynamic storage device capable of storing information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0207] The memory 403 is used to store application code that executes the solution of this application, and its execution is controlled by the processor 401. The processor 401 is used to execute the application code stored in the memory 403 to implement the content shown in the foregoing method embodiments.

[0208] Electronic devices include, but are not limited to: mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (such as in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Servers can also be included. Figure 4 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0209] This application provides a computer-readable storage medium storing a computer program that, when run on a computer, enables the computer to execute the corresponding content in the aforementioned method embodiments. Compared with related technologies, this application provides real-time monitoring of the satellite assembly process by acquiring the progress of each project node in real time. This facilitates the timely detection of project nodes with abnormal completion rates. By reviewing the operational process information of these abnormal project nodes, the cause of the abnormal completion can be determined. After identifying the cause of the abnormal operation, image information at the location of the abnormality is fed back to the terminal devices of relevant personnel. This allows them to view the specific situation at the location of the abnormal operation and quickly determine a response strategy. Real-time monitoring of the satellite assembly work facilitates the timely detection of abnormalities. When an abnormality occurs, image information at the location of the abnormal operation is fed back to the terminal devices of relevant technicians, enabling them to take timely countermeasures. This avoids the need for technicians to continuously monitor the satellite assembly process in real time, thus helping to detect abnormalities promptly and reducing the waste of human resources.

[0210] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0211] The above description is only a partial embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A satellite assembly monitoring method characterized by, include: Real-time acquisition of the current completion status of each project node in satellite assembly; Based on the current completion status of each project node and the complete progress corresponding to each project node, determine whether there are any abnormal project nodes; If there is an abnormal project node, the process information of the abnormal project node is obtained, and the abnormal operation location is determined according to the process information. The abnormal operation location is the abnormal sub-project node in the abnormal project node. Obtain abnormal image information at the location of the abnormal operation; The abnormal image information is then fed back to the terminal devices of relevant personnel; The step of determining whether there are abnormal project nodes based on the current completion status of each project node and the overall progress corresponding to each project node also includes: Based on historical operation data, the operation nature of each project node is determined. The operation nature of each project node includes the difficulty distribution ratio of the assembly work of each project node. In addition, based on historical operation data, similar sub-project nodes of each sub-project node in the project node are determined. The operation nature of the corresponding sub-project node is determined based on the number of participants and processing time of similar sub-project nodes. The operation nature includes difficult and easy. The operation nature of the sub-project node that has both the number of participants and the processing time exceeding the corresponding preset standard value is determined to be difficult. The processing rate for each project node is determined based on the operational nature of each project node. Specifically, based on the current completion status of each project node and the overall progress corresponding to each project node, it is determined whether there are any abnormal project nodes, including: Based on the current completion status and corresponding full progress of each project node, determine the remaining workload of each project node. Based on the remaining workload and corresponding processing efficiency of each project node, predict the remaining working time of each project node. Based on the start time of each project node and the remaining working time, predict the completion date of each project node, where the start time is the working time required to complete the current completion status. Based on the completion date of the project node and the standard completion date of the project node, determine whether the project node is an abnormal project node; The step of determining the processing rate corresponding to each project node based on the operational nature of each project node includes: Based on the ratio of easy to difficult operations for each project node, the operation level of each project node is divided. The operation level is directly proportional to the ratio of easy to difficult operations. The operation level is determined by the proportion of the operation nature of each sub-project node in the project node. Based on the defined operation levels and historical operation data, the processing rate corresponding to each project node is determined. The historical operation data is used to characterize the historical processing rate of each project node in the historical assembly work. The initial processing rate corresponding to each operation level is different, and the operation level and the initial processing rate are inversely proportional. The step of obtaining the process information of the abnormal project node and determining the location of the abnormal operation based on the process information includes: Based on the process information of the abnormal project node, determine at least one processing position corresponding to the abnormal project node; Obtain operation information for each processing location, wherein the operation information includes operation time, operation result, and operation video; The operation information of each processing location is matched with the corresponding operation standard. If they do not match, the processing location is determined to be an abnormal operation location. It also includes: recording the cause of abnormal operation corresponding to the abnormal operation position in each abnormal project node, and forming multiple first matrix data, wherein the first matrix data includes the cause of abnormal operation for at least one abnormal operation position corresponding to the abnormal project node; Multiple first matrix data are integrated to obtain second matrix data, which includes at least one abnormal item node corresponding to the abnormal operation reason at the abnormal operation location; The second matrix data is then fed back to the terminal devices of the relevant staff.

2. The satellite assembly monitoring method according to claim 1, characterized in that, The step of obtaining the abnormal image information at the location of the abnormal operation includes: Obtain a two-dimensional image of the location of the abnormal operation; Determine the three-dimensional coordinates of the abnormal operation location based on the two-dimensional image; Anomaly image information at the location of the abnormal operation is generated based on the three-dimensional coordinates.

3. The satellite assembly monitoring method according to claim 1, characterized in that, Also includes: Obtain the satellite assembly process of the abnormal project node, and based on the obtained satellite assembly process, determine whether the abnormal project node has any influencing nodes, wherein the influencing nodes are project nodes that are related to the abnormal project node. If it exists, then obtain the process information of the affected node; The process information of the affected nodes is compared with the process standard information to generate a verification result, which is then fed back to the terminal devices of the relevant staff.

4. A satellite assembly monitoring device, characterized in that, include: The progress acquisition module is used to acquire the current completion status of each project node in the satellite assembly process in real time. The anomaly detection module is used to determine whether there are any abnormal project nodes based on the current completion status of each project node and the complete progress corresponding to each project node. The abnormal location determination module is used to obtain the process information of the abnormal project node if there is an abnormal project node, and determine the abnormal operation location based on the process information. The abnormal operation location is the sub-project node in the abnormal project node that has an abnormality. An abnormal image acquisition module is used to acquire abnormal image information at the location of the abnormal operation; An anomaly feedback module is used to feed back the abnormal image information to the terminal devices of relevant personnel; The operation nature determination module is used to determine the operation nature of each project node based on historical operation data. The operation nature of each project node includes the difficulty distribution ratio of the assembly work of each project node. Specifically, it determines the similar sub-project nodes of each sub-project node in the project node based on historical operation data, and determines the operation nature of the corresponding sub-project node based on the number of participants and processing time of the similar sub-project nodes. The operation nature includes difficulty and ease. The operation nature of the sub-project node is determined to be difficult if both the number of participants and the processing time exceed the corresponding preset standard value. The processing rate determination module is used to determine the processing rate corresponding to each project node based on the operation nature of each project node. The anomaly detection module, based on the current completion status and the overall progress of each project node, determines whether there are any abnormal project nodes. Specifically, it is used for: Based on the current completion status and corresponding full progress of each project node, determine the remaining workload of each project node. Based on the remaining workload and corresponding processing efficiency of each project node, predict the remaining working time of each project node. Based on the start time of each project node and the remaining working time, predict the completion date of each project node, where the start time is the working time required to complete the current completion status. Based on the completion date of the project node and the standard completion date of the project node, determine whether the project node is an abnormal project node; When determining the processing rate for each project node based on its operational nature, the processing rate determination module is specifically used for: Based on the ratio of easy to difficult operations for each project node, the operation level of each project node is divided. The operation level is directly proportional to the ratio of easy to difficult operations. The operation level is determined by the proportion of the operation nature of each sub-project node in the project node. Based on the defined operation levels and historical operation data, the processing rate corresponding to each project node is determined. The historical operation data is used to characterize the historical processing rate of each project node in the historical assembly work. The initial processing rate corresponding to each operation level is different, and the operation level and the initial processing rate are inversely proportional. When the abnormal location determination module obtains the process information of the abnormal project node and determines the abnormal operation location based on the process information, it is specifically used for: Based on the process information of the abnormal project node, determine at least one processing position corresponding to the abnormal project node; Obtain operation information for each processing location, wherein the operation information includes operation time, operation result, and operation video; The operation information of each processing location is matched with the corresponding operation standard. If they do not match, the processing location is determined to be an abnormal operation location. A first matrix generation module is used to record the cause of abnormal operation corresponding to the abnormal operation position in each abnormal project node, and to form multiple first matrix data, wherein the first matrix data includes the cause of abnormal operation at least one abnormal operation position corresponding to the abnormal project node. A second matrix generation module is used to integrate multiple first matrix data to obtain second matrix data, wherein the second matrix data includes at least one abnormal item node corresponding to the abnormal operation reason at the abnormal operation location; The matrix data feedback module is used to feed back the second matrix data to the terminal devices of relevant staff.

5. An electronic device, characterized in that, The electronic device includes: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application being configured to: perform the satellite assembly monitoring method according to any one of claims 1-3.

6. A computer-readable storage medium, characterized in that, include: The computer program is stored that can be loaded by a processor and executed as described in any one of claims 1-3.

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